What is the primary focus of correlation in statistics?

The primary focus of correlation in statistics is to assess the relationship between two variables. Correlation measures the strength and direction of a linear relationship between these variables, providing insights into how closely related they are. When two variables are correlated, it indicates that as one variable changes, the other variable tends to change in a predictable manner.

This relationship is quantified by the correlation coefficient, which can range from -1 to +1. A correlation of +1 indicates a perfect positive relationship, 0 indicates no relationship, and -1 indicates a perfect negative relationship. Understanding these relationships is essential in many fields, as it can guide decision-making and predictions.

The other options highlight important concepts in statistics but do not accurately describe the main focus of correlation. Determining causation requires more than correlation; it often necessitates experimental or longitudinal studies. Measuring the spread of data pertains to statistical concepts like variance and standard deviation rather than correlation. Visualizing data, while crucial for understanding and communication, does not intrinsically involve the assessment of relationships between variables in the same way that correlation does.